Effects of multiple freeze–thaw cycles on meat quality,nutrients, water distribution and microstructure in bovine rumen smooth muscle

This study investigated the effect of 5 freeze–thaw cycles (freezing at −18°C for 12 h and then thawing at 4°C for approximately 12 h) on the meat quality, proximate composition, water distribution and microstructure of bovine rumen smooth muscle (BSM). As the number of freeze–thaw cycles increased, BSM pH, shear force, water content and protein content decreased by 3.06%, 35.50%, 14.49% and 21.11%, respectively, whereas BSM thawing loss, cooking loss, pressing loss, total aerobic count (TAC), ash content and fat content increased by 108.12%, 47.75%, 78.33%, 90.99%, 105% and 35.20%, respectively. The freeze–thaw cycles resulted in greater protein and lipid oxidation, as evidenced by a 36.46% reduction in the sulfhydryl content and a 209.06% and 338.46% increase in the carbonyl and malondialdehyde contents, respectively. Ice crystal formation disrupted the structural integrity of the muscle tissue. Low-field nuclear magnetic resonance results showed that the freeze–thaw cycles prolonged the relaxation times (T_2b, T₂₁ and T₂₂), indicating that immobile water shifted to free water, and consequently, free water mobility increased. After 3 freeze–thaw cycles, the decline in shear force slowed, the increase in thawing loss became accelerated, and the TAC approached the domain value (6 log colony-forming units/g). Therefore, the number of freeze–thaw cycles of smooth muscle during transport, storage and distribution should be controlled to 3 or fewer. The current results provide a theoretical basis and data support for the further utilisation and culinary processing of smooth muscle.     

Direct shear behavior of gravel-rubber mixtures: Discrete element modeling and microscopic investigations

In this paper, a newly developed 3-dimentional discrete element model (DEM) for gravel-rubber mixtures (GRMs), namely DEM4GRM, that is capable of accurately describing the macro-scale shear response (from small to large deformation) of GRMs in a direct shear box apparatus is presented. Rigid gravel grains are modelled as simple multi-shape clumps, while soft rubber particles are modeled by using deformable 35-ball body-centered-cubic clusters. Mixtures are prepared with different volumetric rubber content (VRC) at 0, 10, 25, 40 and 100%, statically compressed under 30, 60 and 100 kPa vertical stress and then sheared, by closely simulating a reference laboratory test procedure. The variation of micro-scale factors such as fabric, normal and tangential force anisotropy is carefully examined throughout the shearing process and described by means of novel micro-mechanical relationships valid for GRMs. Moreover, strong-force chains are scrutinized to identify the transition from rigid to soft granular skeleton and gain insights on the load transfer and deformation mechanisms of GRMs. It is shown that the development of the fabric and force anisotropy during shearing is closely related to the macro-scale shear strength of GRMs, and strongly depends on the VRC. Besides, strong-force chains appear to be primarily formed by gravel-gravel contacts (resulting in a rigid-like mechanical behavior) up to VRC = 30%, and by rubber-rubber contacts (causing a soft-like mechanical response) beyond VRC = 60%. Alternatively, at 30% < VRC < 60%, gravel-rubber contacts are predominant in the strong-force network and an intermediate mechanical behavior is observed. This is consistent with the behavioral trends observed in the macro- and micro-mechanical responses.     

Effect of the particle size ratio on macro- and mesoscopic shear characteristics of the geogrid-reinforced rubber and sand mixture interface

As a new type of material for civil engineering projects, the rubber and sand mixture is widely used in roadbed fillers, offering environmental benefits over traditional tyre disposal methods. This study uses a large-scale direct shear apparatus to examine the interface shear properties of the geogrid-reinforced rubber and sand mixture, considering different particle size ratios (r), rubber contents, and normal stresses. Based on indoor tests, direct shear models of the mixture with different values of r are established in PFC^3D, revealing the meso-mechanical mechanism of the mixture in the direct shear process. The results show that when r is greater than 1, incorporating a certain amount of rubber particles can increase the shear strength of the mixture. The r values of 15.78, 7.63, and 3.98 correspond to an optimal rubber content of 30%, 10%, and 20%, respectively. When r is less than 1, mixing rubber particles can only reduce the shear strength of the mixture. When the rubber content is low, the smaller the value of r, the greater is the thickness of the shear band. Furthermore, the normal and tangential contact forces are greater. The fabric anisotropy evolution law of the mixture is consistent with the change in the contact force distribution.     

Pullout testing and Particle Image Velocimetry (PIV) analysis of geogrid reinforcement embedded in granular drainage layers

The paper investigates the feasibility of using fine-grained soil as backfill material of geosynthetic-reinforced walls and slopes, through a laboratory study on pullout behavior of geogrids in granular layers. A series of pullout tests was carried out on an HDPE uniaxial geogrid in thin sand and gravel layers that were embedded in clay specimens.Aside from different soil arrangements, the influences of moisture content and overburden pressure on the geogrid pullout behavior is assessed and discussed. The tests were carried out at four different gravimetric water contents (GWC) on the dry and wet sides of the clay optimum moisture content (OMC), and overburden pressure values within the range σ_v = 25–100 kPa. Particle Image Velocimetry (PIV) was used to capture digital images during the tests, which were processed to help with the interpretation and improved understanding of the soil-geogrid interactions at different GWC values. Results show that embedding geogrid reinforcement in layers of sand or gravel can significantly increase the pullout resistance in an otherwise moist clay backfill, and this improved pullout efficiency is greater at higher overburden pressures. The improvement in pullout capacity was observed in clay specimens compacted at both the dry and wet sides of the OMC.     

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).     

Analytical Modeling for Translating Statistical Changes to Circuit Variability by Ultra-Deep Submicron Digital Circuit Design

This paper presents a physics-based compact gate delay model that includes all short-channel phenomena prevalent at the ultra-deep submicron technology node of 32 nm. To simplify calculations, the proposed model is connected to a compact α-power law-based (Sakurai-Newton) model. The model has been tested on a wide range of supply voltages. The model accurately predicts nominal delays and the delays under process variations. It has been shown that at lower technology nodes, the delay is more sensitive to threshold voltage variations, specifically at the sub-threshold operating region as compared with effective channel length variations above the threshold region.     

“方变圆”变径筒状结构滑模施工技术

为解决塔式光热的核心构筑物吸热塔"方变圆"变径超高筒体结构施工难题,选用一套可变形的滑模平台系统,通过操作系统上可调千斤顶支座、门架横向液压千斤顶装置、多处可调节模板角度和收缩模板的丝杆等,使得滑模根据施工需求可在一定的范围内调节模板倾角、间距,并逐步完成收缩变形,其理论滑模允许偏角20°,最终高效完成异形结构施工。该滑模系统刚度大、承载及堆料能力强、空间大、机械化程度高,施工操作简单,安全性高,适应沙漠极端环境。全过程仅需使用一套滑模体系,就能完成方形段、方变圆的变形段及圆形段施工,大大提高了施工效率,为类似环境下相似结构的施工提供了一定的参考。     

Synthesis of thermoresponsive copolymer/silica-coated magnetite nanoparticle composite and its application for heavy metal ion recovery

To enhance chemical stability and suppress of aggregation of magnetite nanoparticles (MNPs), which are used as a support for thermoresponsive copolymer immobilization, silica coating of the MNPs is applied via the electrooxidation method. Although the resulting silica coated-MNPs also formed aggregates, the size distribution of the aggregate shifted to smaller size range. Because of that, the surface area available for copolymer immobilization increased approximately 6.7 times at maximum as compared with that of the uncoated MNPs. It contributed to the increase of the amount of the immobilized copolymer on the silica-coated MNPs, which is approximately four times larger than that on the uncoated MNPs. Fe₃O₄ dissolution test confirmed enhancement of chemical stability of MNPs. The thermoresponsive copolymer immobilized on the silica-coated MNPs shows the ability to recycle Cu(II) ion from Cu(II) containing solution by changing temperature with significantly shorter time than those in other thermoresponsive adsorbents in gel form.     

Centrifugally spun carbon fibers prepared from aqueous poly(vinylpyrrolidone) solutions as binder-free anodes in lithium-ion batteries

Aqueous solutions of poly(vinylpyrrolidone) (PVP) of various concentrations (20, 25, and 28 wt%) were successfully spun into fibers by centrifugal spinning. The pristine PVP fibers were annealed and carbonized to produce flexible carbon fibers for use as binder-free anodes in lithium-ion batteries. These flexible carbon fibers were prepared by developing a novel three-step heat treatment to reduce the residual stresses in the pristine PVP precursor fibers, and to prevent fiber degradation during carbonization. The thermogravimetric analysis data showed that the annealed fibers yielded a residual mass percentage of 36.0% while the pristine PVP fibers suffered a higher mass loss and only retained 26.5% of original mass above 450 °C (under nitrogen). The electrochemical performance of the carbon-fiber anodes was evaluated by conducting galvanostatic charge/discharge, rate performance, and cycle voltammetry experiments. The 20, 25, and 28 wt% derived binder-free anodes delivered specific charge capacities of 205, 189, and 275 mAh g⁻¹, respectively, after the first cycle at a current density of 100 mA g⁻¹. The results obtained in this work indicate that a feasible pathway towards a large-scale production of carbon-fiber anodes from a 100% aqueous solution can be achieved via centrifugal spinning and subsequent heat treatment.